This paper proposes algorithms to reduce the size of firmware updates transmitted over-the-air (FOTA). It uses a three stage approach of chunking files into variable sized pieces, hashing the chunks, and comparing hashes to find similar chunks between versions. This allows creating "delta" updates that only transmit changed parts, rather than full files. The algorithms were able to reduce FOTA delta sizes by up to 30% compared to existing tools on test firmware pairs, saving bandwidth. Experimental results on three firmware pairs demonstrate size reductions and performance compared to Google's existing FOTA update method.
Orion Network Performance Monitor (NPM) Optimization and Tuning TrainingSolarWinds
For more information on NPM, visit: http://www.solarwinds.com/network-performance-monitor.aspx
During this Orion NPM training session, we'll demonstrate the processes for optimizing Orion's performance. We'll cover tuning parameters and procedures for:
• Orion's website
• Orion's SQL database backend
• Orion's data collection services
The information covered in this class will be helpful for those administering Orion servers of all sizes, small and large, who are interested in receiving optimal performance.
Modeling of size reduction, particle size analysis and flow characterisation ...eSAT Journals
Abstract Comparative study using Rosin-Rammler-Sperling-Bennet (RRSB) and Rosin-Rammler model parameters, including particle size analysis and flow characterization helps in identifying whether hammer mill or pin mill is suitable for grinding three selected spices, namely, cinnamon, coriander and turmeric. Model parameters like degree of uniformity in size and statistical average diameter of ground products, mean sizes of ground particles, Bond’s work index, specific energy consumption for grinding, and flow characteristics indicate cinnamon and coriander are suitable for grinding with hammer mill while turmeric is suitable for grinding with pin mill. Keywords: Rosin-Rammler-Sperling-Bennet model, coriander, cinnamon, turmeric, degree of uniformity, statistical average diameter, Bond’s work index, specific energy.
Makalah ini merupakan tugas kelompok dari mata kuliah "Keamanan Komputer". Di dalamnya dibahas mengenai apa pengertian dari fungsi hash, bagaimana sifat-sifat dan apa saja manfaatnya. Kemudian dilanjutkan dengan membahas lebih dalam mengenai salah satu fungsi hash yaitu SHA-256.
An introduction to the SHA Hashing Algorithm. The origins of SHA are explained, along with the family taxonomy of SHA message digest functions. We also cover their uses in cryptography. http://boblandstrom.com
Presentasi ini merupakan presentasi dari makalah dengan judul "Fungsi Hash & Algoritma SHA-256" (http://www.slideshare.net/gustitammam/fungsi-hash-algoritma-sha256). Di dalamnya dibahas mengenai apa pengertian dari fungsi hash, bagaimana sifat-sifat dan apa saja manfaatnya. Kemudian dilanjutkan dengan membahas lebih dalam mengenai salah satu fungsi hash yaitu SHA-256.
Pin Mills are the mills used for grinding variety of things. The working, advantages, disadvantages, specifications and applications of Pin Mills have been well described in the presentation.
Orion Network Performance Monitor (NPM) Optimization and Tuning TrainingSolarWinds
For more information on NPM, visit: http://www.solarwinds.com/network-performance-monitor.aspx
During this Orion NPM training session, we'll demonstrate the processes for optimizing Orion's performance. We'll cover tuning parameters and procedures for:
• Orion's website
• Orion's SQL database backend
• Orion's data collection services
The information covered in this class will be helpful for those administering Orion servers of all sizes, small and large, who are interested in receiving optimal performance.
Modeling of size reduction, particle size analysis and flow characterisation ...eSAT Journals
Abstract Comparative study using Rosin-Rammler-Sperling-Bennet (RRSB) and Rosin-Rammler model parameters, including particle size analysis and flow characterization helps in identifying whether hammer mill or pin mill is suitable for grinding three selected spices, namely, cinnamon, coriander and turmeric. Model parameters like degree of uniformity in size and statistical average diameter of ground products, mean sizes of ground particles, Bond’s work index, specific energy consumption for grinding, and flow characteristics indicate cinnamon and coriander are suitable for grinding with hammer mill while turmeric is suitable for grinding with pin mill. Keywords: Rosin-Rammler-Sperling-Bennet model, coriander, cinnamon, turmeric, degree of uniformity, statistical average diameter, Bond’s work index, specific energy.
Makalah ini merupakan tugas kelompok dari mata kuliah "Keamanan Komputer". Di dalamnya dibahas mengenai apa pengertian dari fungsi hash, bagaimana sifat-sifat dan apa saja manfaatnya. Kemudian dilanjutkan dengan membahas lebih dalam mengenai salah satu fungsi hash yaitu SHA-256.
An introduction to the SHA Hashing Algorithm. The origins of SHA are explained, along with the family taxonomy of SHA message digest functions. We also cover their uses in cryptography. http://boblandstrom.com
Presentasi ini merupakan presentasi dari makalah dengan judul "Fungsi Hash & Algoritma SHA-256" (http://www.slideshare.net/gustitammam/fungsi-hash-algoritma-sha256). Di dalamnya dibahas mengenai apa pengertian dari fungsi hash, bagaimana sifat-sifat dan apa saja manfaatnya. Kemudian dilanjutkan dengan membahas lebih dalam mengenai salah satu fungsi hash yaitu SHA-256.
Pin Mills are the mills used for grinding variety of things. The working, advantages, disadvantages, specifications and applications of Pin Mills have been well described in the presentation.
Data Deduplication: Venti and its improvementsUmair Amjad
Data is the primary thing which is available in digital form everywhere. To store this massive data, the storage methodology should be efficient as well as intelligent enough to find the redundant data to save. Data deduplication techniques are widely used by storage servers to eliminate the possibilities of storing multiple copies of the data. Deduplication identifies duplicate data portions going to be stored in storage systems also removes duplication in existing stored data in storage systems. Hence yield a significant cost saving. This paper is about data deduplication, taking Venti as base case discussed it in detail and also identify area of improvements in Venti which are addressed by other papers.
Google File System was innovatively created by Google engineers and it is ready for production in record time. The success of Google is to attributed the efficient search algorithm, and also to the underlying commodity hardware. As Google run number of application then Google’s goal became to build a vast storage network out of inexpensive commodity hardware. So Google create its own file system, named as Google File System that is GFS. Google File system is one of the largest file system in operation. Generally Google File System is a scalable distributed file system of large distributed data intensive apps. In the design phase of Google file system, in which the given stress includes component failures , files are huge and files are mutated by appending data. The entire file system is organized hierarchically in directories and identified by pathnames. The architecture comprises of multiple chunk servers, multiple clients and a single master. Files are divided into chunks, and that is the key design parameter. Google File System also uses leases and mutation order in their design to achieve atomicity and consistency. As of there fault tolerance, Google file system is highly available, replicas of chunk servers and master exists.
Google File System was innovatively created by Google engineers and it is ready for production in record time. The success of Google is to attributed the efficient search algorithm, and also to the underlying commodity hardware. As Google run number of application then Google’s goal became to build a vast storage network out of inexpensive commodity hardware. So Google create its own file system, named as Google File System that is GFS. Google File system is one of the largest file system in operation. Generally Google File System is a scalable distributed file system of large distributed data intensive apps. In the design phase of Google file system, in which the given stress includes component failures , files are huge and files are mutated by appending data. The entire file system is organized hierarchically in directories and identified by pathnames. The architecture comprises of multiple chunk servers, multiple clients and a single master. Files are divided into chunks, and that is the key design parameter. Google File System also uses leases and mutation order in their design to achieve atomicity and consistency. As of there fault tolerance, Google file system is highly available, replicas of chunk servers and master exists.
Efficient load rebalancing for distributed file system in CloudsIJERA Editor
Cloud computing is an upcoming era in software industry. It’s a very vast and developing technology.
Distributed file systems play an important role in cloud computing applications based on map reduce
techniques. While making use of distributed file systems for cloud computing, nodes serves computing and
storage functions at the same time. Given file is divided into small parts to use map reduce algorithms in
parallel. But the problem lies here since in cloud computing nodes may be added, deleted or modified any time
and also operations on files may be done dynamically. This causes the unequal load distribution of load among
the nodes which leads to load imbalance problem in distributed file system. Newly developed distributed file
system mostly depends upon central node for load distribution but this method is not helpful in large-scale and
where chances of failure are more. Use of central node for load distribution creates a problem of single point
dependency and chances of performance of bottleneck are more. As well as issues like movement cost and
network traffic caused due to migration of nodes and file chunks need to be resolved. So we are proposing
algorithm which will overcome all these problems and helps to achieve uniform load distribution efficiently. To
verify the feasibility and efficiency of our algorithm we will be using simulation setup and compare our
algorithm with existing techniques for the factors like load imbalance factor, movement cost and network traffic.
A New Architecture for Group Replication in Data GridEditor IJCATR
Nowadays, grid systems are vital technology for programs running with high performance and problems solving with largescale
in scientific, engineering and business. In grid systems, heterogeneous computational resources and data should be shared
between independent organizations that are scatter geographically. A data grid is a kind of grid types that make relations computational
and storage resources. Data replication is an efficient way in data grid to obtain high performance and high availability by saving
numerous replicas in different locations e.g. grid sites. In this research, we propose a new architecture for dynamic Group data
replication. In our architecture, we added two components to OptorSim architecture: Group Replication Management component
(GRM) and Management of Popular Files Group component (MPFG). OptorSim developed by European Data Grid projects for
evaluate replication algorithm. By using this architecture, popular files group will be replicated in grid sites at the end of each
predefined time interval.
Bioinformatics may be defined as the field of science
in which biology, computer science, and information
technology merge to form a single discipline. Its ultimate
goal is to enable the discovery of new biological insights as
well as to create a global perspective from which unifying
principles in biology can be discerned by means of
bioinformatics tools for storing, retrieving, organizing and
analyzing biological data. Also most of these tools possess
very distinct features and capabilities making a direct
comparison difficult to be done. In this paper we propose
taxonomy for characterizing bioinformatics tools and briefly
surveys major bioinformatics tools under each categories.
Hopefully this study will stimulate other designers
and
experienced end users understand the details of particular
tool categories/tools, enabling them to make the best choices
for their particular research interests.
A Strategy for Improving the Performance of Small Files in Openstack Swift Editor IJCATR
This is an effective way to improve the storage access performance of small files in Openstack Swift by adding an aggregate storage module. Because Swift will lead to too much disk operation when querying metadata, the transfer performance of plenty of small files is low. In this paper, we propose an aggregated storage strategy (ASS), and implement it in Swift. ASS comprises two parts which include merge storage and index storage. At the first stage, ASS arranges the write request queue in chronological order, and then stores objects in volumes. These volumes are large files that are stored in Swift actually. During the short encounter time, the object-to-volume mapping information is stored in Key-Value store at the second stage. The experimental results show that the ASS can effectively improve Swift's small file transfer performance.
Text categorization is a term that has intrigued researchers for quite some time now. It is the concept
in which news articles are categorized into specific groups to cut down efforts put in manually categorizing
news articles into particular groups. A growing number of statistical classification and machine learning
technique have been applied to text categorization. This paper is based on the automatic text categorization
of news articles based on clustering using k-mean algorithm. The goal of this paper is to automatically
categorize news articles into groups. Our paper mostly concentrates on K-mean for clustering and for term
frequency we are going to use TF-IDF dictionary is applied for categorization. This is done using mahaout
as platform.
Text document clustering and similarity detection is the major part of document management, where every document should be identified by its key terms and domain knowledge. Based on the similarity, the documents are grouped into clusters. For document similarity calculation there are several approaches were proposed in the existing system. But the existing system is either term based or pattern based. And those systems suffered from several problems. To make a revolution in this challenging environment, the proposed system presents an innovative model for document similarity by applying back propagation time stamp algorithm. It discovers patterns in text documents as higher level features and creates a network for fast grouping. It also detects the most appropriate patterns based on its weight and BPTT performs the document similarity measures. Using this approach, the document can be categorized easily. In order to perform the above, a new approach is used. This helps to reduce the training process problems. The above framework is named as BPTT. The BPTT has implemented and evaluated using dot net platform with different set of datasets.
Resist Dictionary Attacks Using Password Based Protocols For Authenticated Ke...IJERA Editor
A parallel file system is a type of distributed file system that distributes file data across multiple servers and
provides for concurrent access by multiple tasks of a parallel application. In many to many communications or
multiple tasks, key establishments are a major problem in parallel file system. So we propose a variety of
authenticated key exchange protocols that are designed to address the above issue. In this paper, we also study
the password-based protocols for authenticated key exchange (AKE) to resist dictionary attacks. Password-based
protocols for authenticated key exchange (AKE) are designed to work to resist the use of passwords drawn from
a space so small that attacker might well specify, off line, all possible passwords. While many such protocols
have been suggested, the elemental theory has been lagging. We commence by interpreting a model for this
problem, to approach password guessing, forward secrecy, server compromise, and loss of session keys.
BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value S...dbpublications
Nowadays, cloud-based storage services are rapidly growing and becoming an emerging trend in data storage field. There are many problems when designing an efficient storage engine for cloud-based systems with some requirements such as big-file processing, lightweight meta-data, low latency, parallel I/O, Deduplication, distributed, high scalability. Key-value stores played an important role and showed many advantages when solving those problems. This paper presents about Big File Cloud (BFC) with its algorithms and architecture to handle most of problems in a big-file cloud storage system based on key value store. It is done by proposing low-complicated, fixed-size meta-data design, which supports fast and highly-concurrent, distributed file I/O, several algorithms for resumable upload, download and simple data Deduplication method for static data. This research applied the advantages of ZDB - an in-house key value store which was optimized with auto-increment integer keys for solving big-file storage problems efficiently. The results can be used for building scalable distributed data cloud storage that support big-file with size up to several terabytes.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
More Related Content
Similar to Fota Delta Size Reduction Using FIle Similarity Algorithms
Data Deduplication: Venti and its improvementsUmair Amjad
Data is the primary thing which is available in digital form everywhere. To store this massive data, the storage methodology should be efficient as well as intelligent enough to find the redundant data to save. Data deduplication techniques are widely used by storage servers to eliminate the possibilities of storing multiple copies of the data. Deduplication identifies duplicate data portions going to be stored in storage systems also removes duplication in existing stored data in storage systems. Hence yield a significant cost saving. This paper is about data deduplication, taking Venti as base case discussed it in detail and also identify area of improvements in Venti which are addressed by other papers.
Google File System was innovatively created by Google engineers and it is ready for production in record time. The success of Google is to attributed the efficient search algorithm, and also to the underlying commodity hardware. As Google run number of application then Google’s goal became to build a vast storage network out of inexpensive commodity hardware. So Google create its own file system, named as Google File System that is GFS. Google File system is one of the largest file system in operation. Generally Google File System is a scalable distributed file system of large distributed data intensive apps. In the design phase of Google file system, in which the given stress includes component failures , files are huge and files are mutated by appending data. The entire file system is organized hierarchically in directories and identified by pathnames. The architecture comprises of multiple chunk servers, multiple clients and a single master. Files are divided into chunks, and that is the key design parameter. Google File System also uses leases and mutation order in their design to achieve atomicity and consistency. As of there fault tolerance, Google file system is highly available, replicas of chunk servers and master exists.
Google File System was innovatively created by Google engineers and it is ready for production in record time. The success of Google is to attributed the efficient search algorithm, and also to the underlying commodity hardware. As Google run number of application then Google’s goal became to build a vast storage network out of inexpensive commodity hardware. So Google create its own file system, named as Google File System that is GFS. Google File system is one of the largest file system in operation. Generally Google File System is a scalable distributed file system of large distributed data intensive apps. In the design phase of Google file system, in which the given stress includes component failures , files are huge and files are mutated by appending data. The entire file system is organized hierarchically in directories and identified by pathnames. The architecture comprises of multiple chunk servers, multiple clients and a single master. Files are divided into chunks, and that is the key design parameter. Google File System also uses leases and mutation order in their design to achieve atomicity and consistency. As of there fault tolerance, Google file system is highly available, replicas of chunk servers and master exists.
Efficient load rebalancing for distributed file system in CloudsIJERA Editor
Cloud computing is an upcoming era in software industry. It’s a very vast and developing technology.
Distributed file systems play an important role in cloud computing applications based on map reduce
techniques. While making use of distributed file systems for cloud computing, nodes serves computing and
storage functions at the same time. Given file is divided into small parts to use map reduce algorithms in
parallel. But the problem lies here since in cloud computing nodes may be added, deleted or modified any time
and also operations on files may be done dynamically. This causes the unequal load distribution of load among
the nodes which leads to load imbalance problem in distributed file system. Newly developed distributed file
system mostly depends upon central node for load distribution but this method is not helpful in large-scale and
where chances of failure are more. Use of central node for load distribution creates a problem of single point
dependency and chances of performance of bottleneck are more. As well as issues like movement cost and
network traffic caused due to migration of nodes and file chunks need to be resolved. So we are proposing
algorithm which will overcome all these problems and helps to achieve uniform load distribution efficiently. To
verify the feasibility and efficiency of our algorithm we will be using simulation setup and compare our
algorithm with existing techniques for the factors like load imbalance factor, movement cost and network traffic.
A New Architecture for Group Replication in Data GridEditor IJCATR
Nowadays, grid systems are vital technology for programs running with high performance and problems solving with largescale
in scientific, engineering and business. In grid systems, heterogeneous computational resources and data should be shared
between independent organizations that are scatter geographically. A data grid is a kind of grid types that make relations computational
and storage resources. Data replication is an efficient way in data grid to obtain high performance and high availability by saving
numerous replicas in different locations e.g. grid sites. In this research, we propose a new architecture for dynamic Group data
replication. In our architecture, we added two components to OptorSim architecture: Group Replication Management component
(GRM) and Management of Popular Files Group component (MPFG). OptorSim developed by European Data Grid projects for
evaluate replication algorithm. By using this architecture, popular files group will be replicated in grid sites at the end of each
predefined time interval.
Bioinformatics may be defined as the field of science
in which biology, computer science, and information
technology merge to form a single discipline. Its ultimate
goal is to enable the discovery of new biological insights as
well as to create a global perspective from which unifying
principles in biology can be discerned by means of
bioinformatics tools for storing, retrieving, organizing and
analyzing biological data. Also most of these tools possess
very distinct features and capabilities making a direct
comparison difficult to be done. In this paper we propose
taxonomy for characterizing bioinformatics tools and briefly
surveys major bioinformatics tools under each categories.
Hopefully this study will stimulate other designers
and
experienced end users understand the details of particular
tool categories/tools, enabling them to make the best choices
for their particular research interests.
A Strategy for Improving the Performance of Small Files in Openstack Swift Editor IJCATR
This is an effective way to improve the storage access performance of small files in Openstack Swift by adding an aggregate storage module. Because Swift will lead to too much disk operation when querying metadata, the transfer performance of plenty of small files is low. In this paper, we propose an aggregated storage strategy (ASS), and implement it in Swift. ASS comprises two parts which include merge storage and index storage. At the first stage, ASS arranges the write request queue in chronological order, and then stores objects in volumes. These volumes are large files that are stored in Swift actually. During the short encounter time, the object-to-volume mapping information is stored in Key-Value store at the second stage. The experimental results show that the ASS can effectively improve Swift's small file transfer performance.
Text categorization is a term that has intrigued researchers for quite some time now. It is the concept
in which news articles are categorized into specific groups to cut down efforts put in manually categorizing
news articles into particular groups. A growing number of statistical classification and machine learning
technique have been applied to text categorization. This paper is based on the automatic text categorization
of news articles based on clustering using k-mean algorithm. The goal of this paper is to automatically
categorize news articles into groups. Our paper mostly concentrates on K-mean for clustering and for term
frequency we are going to use TF-IDF dictionary is applied for categorization. This is done using mahaout
as platform.
Text document clustering and similarity detection is the major part of document management, where every document should be identified by its key terms and domain knowledge. Based on the similarity, the documents are grouped into clusters. For document similarity calculation there are several approaches were proposed in the existing system. But the existing system is either term based or pattern based. And those systems suffered from several problems. To make a revolution in this challenging environment, the proposed system presents an innovative model for document similarity by applying back propagation time stamp algorithm. It discovers patterns in text documents as higher level features and creates a network for fast grouping. It also detects the most appropriate patterns based on its weight and BPTT performs the document similarity measures. Using this approach, the document can be categorized easily. In order to perform the above, a new approach is used. This helps to reduce the training process problems. The above framework is named as BPTT. The BPTT has implemented and evaluated using dot net platform with different set of datasets.
Resist Dictionary Attacks Using Password Based Protocols For Authenticated Ke...IJERA Editor
A parallel file system is a type of distributed file system that distributes file data across multiple servers and
provides for concurrent access by multiple tasks of a parallel application. In many to many communications or
multiple tasks, key establishments are a major problem in parallel file system. So we propose a variety of
authenticated key exchange protocols that are designed to address the above issue. In this paper, we also study
the password-based protocols for authenticated key exchange (AKE) to resist dictionary attacks. Password-based
protocols for authenticated key exchange (AKE) are designed to work to resist the use of passwords drawn from
a space so small that attacker might well specify, off line, all possible passwords. While many such protocols
have been suggested, the elemental theory has been lagging. We commence by interpreting a model for this
problem, to approach password guessing, forward secrecy, server compromise, and loss of session keys.
BFC: High-Performance Distributed Big-File Cloud Storage Based On Key-Value S...dbpublications
Nowadays, cloud-based storage services are rapidly growing and becoming an emerging trend in data storage field. There are many problems when designing an efficient storage engine for cloud-based systems with some requirements such as big-file processing, lightweight meta-data, low latency, parallel I/O, Deduplication, distributed, high scalability. Key-value stores played an important role and showed many advantages when solving those problems. This paper presents about Big File Cloud (BFC) with its algorithms and architecture to handle most of problems in a big-file cloud storage system based on key value store. It is done by proposing low-complicated, fixed-size meta-data design, which supports fast and highly-concurrent, distributed file I/O, several algorithms for resumable upload, download and simple data Deduplication method for static data. This research applied the advantages of ZDB - an in-house key value store which was optimized with auto-increment integer keys for solving big-file storage problems efficiently. The results can be used for building scalable distributed data cloud storage that support big-file with size up to several terabytes.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Similar to Fota Delta Size Reduction Using FIle Similarity Algorithms (20)